Evidence map›Paper›PMID 38703875›Full record

ArticleJournal of stroke and cerebrovascular diseases : the official journal of National Stroke Association2024

Multicenter comparison using two AI stroke CT perfusion software packages for determining thrombectomy eligibility.

Benjamin T Alwood, Dawn M Meyer, Chip Ionita, Kenneth V Snyder, Roberta Santos, Lindsey Perrotta, Ryan Crooks, Kimberlee Van Orden, Dolores Torres, Briana Poynor and 4 more

Abstract readMulticenter StudyComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
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  5. Review
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  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Benjamin T AlwoodDepartment of Vascular Neurology, University of Florida, Jacksonville, FL, United States; University of California San Diego Stroke Center, University of California San Diego, San Diego, CA, United States. Electronic address: benjamin.alwood@jax.ufl.edu.
Dawn M MeyerUniversity of California San Diego Stroke Center, University of California San Diego, San Diego, CA, United States.
Chip IonitaDepartment of Biomedical Engineering and Neurosurgery, University at Buffalo, Buffalo NY, United States.
Kenneth V SnyderDepartment of Biomedical Engineering and Neurosurgery, University at Buffalo, Buffalo NY, United States.
Roberta SantosDepartment of Vascular Neurology, University of Florida, Jacksonville, FL, United States.
Lindsey PerrottaDepartment of Vascular Neurology, University of Florida, Jacksonville, FL, United States.
Ryan CrooksDepartment of Vascular Neurology, University of Florida, Jacksonville, FL, United States.
Kimberlee Van OrdenUniversity of California San Diego Stroke Center, University of California San Diego, San Diego, CA, United States.
Dolores TorresUniversity of California San Diego Stroke Center, University of California San Diego, San Diego, CA, United States.
Briana PoynorUniversity of California San Diego Stroke Center, University of California San Diego, San Diego, CA, United States.
Nhan PhamDepartment of Radiology, University of California San Diego, San Diego, CA, United States.
Sophie KellyDepartment of Radiology, University of California San Diego, San Diego, CA, United States.
Brett C MeyerUniversity of California San Diego Stroke Center, University of California San Diego, San Diego, CA, United States.
Divya S BolarDepartment of Radiology, University of California San Diego, San Diego, CA, United States; Center for Functional MRI, University of California San Diego, San Diego, CA, United States.

Funding

San Diego StrokeNet Regional Coordinating CenterU24NS107225 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BRETT C MEYER · 2018 to 2026
$2.4M
NINDS NIH HHS U24 NS107225
6 · The paper itself

Abstract

backgroundStroke AI platforms assess infarcted core and potentially salvageable tissue (penumbra) to identify patients suitable for mechanical thrombectomy. Few studies have compared outputs of these platforms, and none have been multicenter or considered NIHSS or scanner/protocol differences. Our objective was to compare volume estimates and thrombectomy eligibility from two widely used CT perfusion (CTP) packages, Viz.ai and RAPID.AI, in a large multicenter cohort.

methodsWe analyzed CTP data of acute stroke patients with large vessel occlusion (LVO) from four institutions. Core and penumbra volumes were estimated by each software and DEFUSE-3 thrombectomy eligibility assessed. Results between software packages were compared and categorized by NIHSS score, scanner manufacturer/model, and institution.

resultsPrimary analysis of 362 cases found statistically significant differences in both software's volume estimations, with subgroup analysis showing these differences were driven by results from a single scanner model, the Canon Aquilion One. Viz.ai provided larger estimates with mean differences of 8cc and 18cc for core and penumbra, respectively (p<0.001). NIHSS subgroup analysis also showed systematically larger Viz.ai volumes (p<0.001). Despite volume differences, a significant difference in thrombectomy eligibility was not found. Additional subgroup analysis showed significant differences in penumbra volume for the Phillips Ingenuity scanner, and thrombectomy eligibility for the Canon Aquilion One scanner at one center (7 % increased eligibility with Viz.ai, p=0.03).

conclusionsDespite systematic differences in core and penumbra volume estimates between Viz.ai and RAPID.AI, DEFUSE-3 eligibility was not statistically different in primary or NIHSS subgroup analysis. A DEFUSE-3 eligibility difference, however, was seen on one scanner at one institution, suggesting scanner model and local CTP protocols can influence performance and cause discrepancies in thrombectomy eligibility. We thus recommend centers discuss optimal scanning protocols with software vendors and scanner manufacturers to maximize CTP accuracy.

Indexed as

Cerebrovascular CirculationPatient SelectionPerfusion ImagingPredictive Value of TestsRadiographic Image Interpretation, Computer-AssistedSoftwareThrombectomyAgedAged, 80 and overClinical Decision-MakingComputed Tomography AngiographyFemaleHumansIschemic StrokeMaleMiddle AgedAcute strokeCT PerfusionDEFUSE-3, Mechanical thrombectomyInterventional neuroradiologyIschemic stroke

Identifiers

PMID38703875
PMCPMC11366438

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.